#!/usr/bin/env python2
# -*- coding: utf-8 -*-
"""
Created on Fri Sep  1 17:15:57 2017

@author: hhw
"""

#!/usr/bin/env python2
# -*- coding: utf-8 -*-
# 导入必要的软件包
#import imutils
import cv2
'''
# 创建参数解析器并解析参数
ap = argparse.ArgumentParser()
ap.add_argument("-v", "--video", help="path to the video file")
ap.add_argument("-a", "--min-area", type=int, default=500, help="minimum area size")
args = vars(ap.parse_args())
 
# 如果video参数为None，那么我们从摄像头读取数据
if args.get("video", None) is None:
    camera = cv2.VideoCapture(0)
    time.sleep(0.25)
 
# 否则我们读取一个视频文件
else:
    camera = cv2.VideoCapture(args["video"])
 
# 初始化视频流的第一帧
'''

"bike.avi"
camera=cv2.VideoCapture("./monitor35.avi")
firstFrame = None
tubecreatingfrequency=5
tubecreatingwaitline=0
tubenumbers=0
trackingmethods=("KCF","MIL","BOOSTING","MEDIANFLOW","TLD")
trackingmethod=trackingmethods[2]#maximum 4
#"KCF"：目标人物与其他人在画面上大面积交错以后，会出现跟踪错误
#"MIL"：速度慢
#"BOOSTING"：非常慢，显示严重卡顿
#"MEDIANFLOW"：比较流畅，但是跟踪效果差
#"TLD"：非常慢，自动调整跟踪目标的大小（框），在目标周围没有明显干扰的情况下，也会跟踪错误

process_state="detecting"
if False == camera.isOpened():  
    print 'open video failed'  
else:  
    print 'open video succeeded'    
# 遍历视频的每一帧

# 获取当前帧并初始化occupied/unoccupied文本
while True:
    # 获取当前帧并初始化occupied/unoccupied文本
    (grabbed, frame) = camera.read()
    
    # 如果不能抓取到一帧，说明我们到了视频的结尾
    if not grabbed:
        print 'not grabbed'   
        break
    
    if process_state=="detecting":
        # 调整该帧的大小，转换为灰阶图像并且对其进行高斯模糊
        #frame = imutils.resize(frame, width=500)
        gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
        gray = cv2.GaussianBlur(gray, (21, 21), 0)
     
        # 如果第一帧是None，对其进行初始化
        if firstFrame is None:
            firstFrame = gray
            continue
        # 计算当前帧和第一帧的不同
        frameDelta = cv2.absdiff(firstFrame, gray)
        thresh = cv2.threshold(frameDelta, 25, 255, cv2.THRESH_BINARY)[1]
     
        # 扩展阀值图像填充孔洞，然后找到阀值图像上的轮廓
        thresh = cv2.dilate(thresh, None, iterations=2)
        (binary,cnts, _) = cv2.findContours(thresh.copy(), cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
     
        # 遍历轮廓q
        for c in cnts:
            # if the contour is too small, ignore it
            #if cv2.contourArea(c) < args["min_area"]:
            #    continue
     
            # compute the bounding box for the contour, draw it on the frame,
            # and update the text
            # 计算轮廓的边界框，在当前帧中画出该框
            (x, y, w, h) = cv2.boundingRect(c)
            cv2.rectangle(frame, (x, y), (x + w, y + h), (0, 255, 0), 2)
            break
            #if w>10 and h>10:
                #process_state="tracinginit"
    
    if w>10 and h>10:
        tubecreatingwaitline+=1
        if tubecreatingwaitline==tubecreatingfrequency:
            tubecreatingwaitline=0
            tubeimage=frame[y:y+h,x:x+w]
            tubenumbers+=1
            cv2.imwrite("./tube%d.png"%tubenumbers, tubeimage, [int(cv2.IMWRITE_PNG_COMPRESSION), 0])  
    
    if process_state=="tracinginit":
        bbox=(x,y,w,h)
        tracker = cv2.Tracker_create(trackingmethod)
        ok = tracker.init(frame, bbox)
        if not ok:
            print("tracker init failed")
            break
        process_state="tracing"
    
    if process_state=="tracing":
        ok, bbox = tracker.update(frame)
        p1 = (int(bbox[0]), int(bbox[1]))
        p2 = (int(bbox[0] + bbox[2]), int(bbox[1] + bbox[3]))
        cv2.rectangle(frame, p1, p2, (0, 0, 255))

    cv2.imshow("Tracking", frame)
    
    key = cv2.waitKey(100) & 0xFF
 
    # 如果q键被按下，跳出循环
    if key == ord("q"):
        break
    
'''
# draw the text and timestamp on the frame
    # 在当前帧上写文字以及时间戳
    cv2.putText(frame, "Room Status: {}".format(text), (10, 20),
        cv2.FONT_HERSHEY_SIMPLEX, 0.5, (0, 0, 255), 2)
    cv2.putText(frame, datetime.datetime.now().strftime("%A %d %B %Y %I:%M:%S%p"),
        (10, frame.shape[0] - 10), cv2.FONT_HERSHEY_SIMPLEX, 0.35, (0, 0, 255), 1)
 
   # 显示当前帧并记录用户是否按下按键
    cv2.imshow("Security Feed", frame)
    cv2.imshow("Thresh", thresh)
    cv2.imshow("Frame Delta", frameDelta)
'''


 
# 清理摄像机资源并关闭打开的窗口
camera.release()
cv2.destroyAllWindows()
